Deformable image registration based on an image mask generated based on a two-dimensional (2D) computed tomography (CT) image

ABSTRACT

In accordance with at least some embodiments of the present disclosure, a process to improve computed tomography (CT) to cone beam computed tomography (CBCT) registration is disclosed. The process may include receiving a CT image generated by CT-scanning of an object, and receiving a CBCT image generated by CBCT-scanning of the object. The process may include generating an image mask based on Digital Imaging and Communications in Medicine (DICOM) information extracted from the CBCT image. For a specific pixel in the CBCT image, the image mask contains a corresponding data-field indicating whether the specific pixel contains image data generated based on the CBCT-scanning of the object. The process may further include generating a registered image by utilizing the image mask to perform a DIR between the CT image and the CBCT image.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application under 35 U.S.C. §120 of U.S. application Ser. No. 15/935,044 filed Mar. 25, 2018, nowU.S. Pat. No. 10,902,621. The aforementioned U.S. application, includingany appendices or attachments thereof, is hereby incorporated byreference in its entirety.

BACKGROUND

Unless otherwise indicated herein, the approaches described in thissection are not prior art to the claims in this application and are notadmitted to be prior art by inclusion in this section.

The deformable (non-rigid) image registration of a Computed Tomography(CT) image to a Cone Beam Computed Tomography (CBCT) image is animportant operation in, for example, treatment planning, monitoring, andplan adaptation. The goal of the deformable image registration is todeform or warp one image to match another image as accurately aspossible. In some situations, one image may contain a partial field ofview of the scanning object, or with an image boundary that falselyresembles a skin-to-air interface. When performing automaticregistration processing using this image and other images that containthe entire anatomy of a scanning object within the field of view of theimage, the automatic registration processing may generate misleadingcues and lead to wrong registration results. Such an outcome will have asubstantial impact on the accuracy and reliability of automatized stepsin treatment planning and monitoring.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows a Computed Tomography (CT) scanner performing CT scanningoperations;

FIG. 1B shows a Cone Beam Computed Tomography (CBCT) scanner performingCBCT scanning operations;

FIG. 2 shows a block diagram illustrating an exemplary system configuredto improve CT to CBCT registration;

FIG. 3 illustrates details of a registration-enhancement system forimproving CT to CBCT registration;

FIG. 4 illustrates an example scenario to construct and utilize an imagemask during an enhanced Deformable Image Registration (DIR) operation;and

FIG. 5 shows a flow diagram illustrating one embodiment of a process toimprove CT to CBCT registration, all in accordance with certainembodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe Figures, can be arranged, substituted, combined, and designed in awide variety of different configurations, all of which are explicitlycontemplated herein.

FIG. 1A shows a Computed Tomography (CT) scanner performing CT scanningoperations, in accordance with certain embodiments of the presentdisclosure. Throughout the disclosure, the term “CT image” may broadlyrefer to a graphical image containing two-dimensional (2D) medical datagenerated from a single CT scanning operation. A “CT scanning operation”may include multiple “CT scanning interrogations” operating frommultiple angles/directions, and may generate a set of corresponding CTprojections. A CT reconstruction process may then generate one or moreCT images based on this set of CT projections. Likewise, the term “CBCTimage” may broadly refer to a graphical image containing 2D medical datagenerated from a single CBCT scanning operation, and a “CBCT scanningoperation” may include multiple “CBCT scanning interrogations” operatingfrom multiple angles/directions, and may generate a set of correspondingCBCT projections. A CBCT reconstruction process may then generate one ormore CBCT images based on this set of CBCT projections.

In some embodiments, a CT scanner 101 may have, among other components,a beam source 110 and a detector panel 130. The beam source 110 may emita beam 111 of particles (e.g., photons and/or electrons) toward ascanning object 120 (e.g., a patient) placed between the beam source 110and the detector panel 130. The emitted particles may interact with thescanning object 120 through photo-electric absorptions, Rayleigh (orcoherent) scattering, and Compton (or incoherent) scattering, and may ormay not be detected by the detector panel 130 afterward.

In some embodiments, the detector panel 130 may be configured forsensing those particles passed through the scanning object 120 and/orreached the detector panel 130. The detector panel 130 may containmultiple pixels forming a long and narrow grid. Each pixel may detectthe radioactive energy from the particles reaching the pixel, and thedetector panel 130 may utilize the deposited energies detected by allthe pixels to generate one or more CT projections. In some cases, thedetector panel 130 may be flat (as shown in FIG. 1A), or may have an arcshape.

In some embodiments, during a single CT scanning interrogation, the beamsource 110 may project particles towards the detector panel 130 at aparticular angle/direction, and the CT scanner 101 may generate a singleCT projection, based on the particles detected by the detector panel130. Each CT projection may contain 2D image data illustrating thecross-sectional internal structure of the scanning object 120 from theparticular angle/direction. Afterward, the beam source-detector panel(source-detector pair) may be rotated to a different angle/direction toperform another round of CT scanning interrogation of the scanningobject 120, for the CT scanner 101 to generate another CT projection.

In some embodiments, the particles projected from the beam source 110may form a fan-shaped beam (fan beam) having a narrow beam-width in onedimension and a wider beam-width in the other dimension. A CT scanningoperation may include the source-detector pair rotating and traveling ina helix/spiral fashion to traverse the whole scanning object 120 andgenerating a set of CT projections. The set of CT projections may beused in a subsequent reconstruction process to generate one or more CTimages.

FIG. 1B shows a Cone Beam Computed Tomography (CBCT) scanner performingCBCT scanning operations, in accordance with certain embodiments of thepresent disclosure. Similar to the CT scanner 101 of FIG. 1A, the CBCTscanner 102 may have, among other components, a beam source 140 and adetector panel 160. The beam source 140 may emit a beam 141 of particlestoward a scanning object 150 (e.g., a patient) placed between the beamsource 140 and the detector panel 160. The beam source 140 and thedetector panel 160 may be fixated on a gantry which rotates around thescanning object 150 positioned near its middle. The detector panel 160may be configured for sensing those particles passed through thescanning object 150 and/or reached the detector panel 160. The detectorpanel 160 may contain multiple particle-sensing pixels forming asubstantially square grid, and may utilize the deposited energiesdetected by the pixels to generate a CBCT projection.

In some embodiments, during a single CBCT scanning interrogation, thebeam source 140 may project particles towards the detector panel 160 ina particular angle/direction, and the CBCT scanner 102 may generate asingle CBCT projection based on the particles detected by the detectorpanel 160. Each CBCT projection may contain 2D image data representingthe internal structure of the scanning object 150 from the particularangle/direction. Afterward, the beam source-detector panel(source-detector pair) may be rotated to a different angle/direction toperform another round of CBCT scanning interrogation of the scanningobject 150, thereby allowing the CBCT scanner 102 to generate anotherCBCT projection. The CBCT scanner 102 may control the source-detectorpair to rotate around the scanning object 150 in one circle, andgenerate a set of multiple sequential, planar CBCT projections. The setof CBCT projections may be used in a subsequent reconstruction processto generate one or more CBCT images.

In some embodiments, as shown in FIG. 1B, the particles emitted from thebeam source 140 may form a pyramidal-shaped or cone-shaped beam (conicalbeam) which covers the entire scanning object 150 (or covers the entirearea-of-interest of the scanning object 150). Specifically, the beam 141may lead to the generating of a planar projection on the detector panel160 with a field of view (FOV) of the whole scanning object 150. Inother words, each CBCT projection generated by the CBCT scanner 102 mayincorporate the entire FOV of the scanning object 150, while each CTprojection generated by the CT scanner 101 may only show a slice of theFOV.

In some embodiments, during a CBCT scanning interrogation, a conicalbeam of the CBCT scanner 102 may form a substantially-circularilluminated region 161 on the detector panel 160, as the particlesemitted from the beam source 140 may be within the boundary of theconical beam and may mostly reach those pixels of the detector panel 160that are within the illuminated region 161. In other words, the pixelsof the detector panel 160 that are outside of the illuminated region 161may either not detect any particles generated by the beam source 140, ormay detect those particles that are reflected or scattered by thescanning object 150. Thus, the CBCT scanner 102 may generate a CBCTprojection that also has such an illuminated region, and any image datathat are inside of this illuminated region in the CBCT projection may bedeemed meaningful and valid, and any image data outside of thisilluminated region in the CBCT projection may be deemed void,incidental, meaningless, or unreliable.

In some embodiments, the illuminated region 161 may also be related tothe size of the detector panel 160 utilized by the CBCT scanner 102. Inother words, the detector panel 160 is not large enough to cover thewhole illuminated region 161, thereby indirectly resulting in a limitedFOV for the CBCT projections generated by the CBCT scanner 102. In thiscase, the CBCT projection may seem to have a somewhat limited“illuminated region,” as some of the image data that are outside of thecoverage of the detector panel 160 may also be void and meaningless.

In some embodiments, one approach to generate a CT image mayalgorithmically reconstruct a three-dimensional (3D) volume of thescanning object 120 from multiple CT projections obtained via a helicalprogression, and CT images may be generated by “slicing” through this 3Dvolume. Alternatively, another reconstruction process may includeback-projecting multiple CT projections to generate a corresponding CTimage. Likewise, multiple CBCT projections obtained via one rotationalsequence of the CBCT gantry may go through similar image reconstructionprocesses to generate one or more CBCT images. Regardless of thereconstruction processes, the generated CT images and/or CBCT images mayalways be affected by factors such as whole-or-partial FOV andilluminated regions that are inherent in the CT projections and CBCTprojections.

In some embodiments, the scanning object 120 may be subjected to ahigher amount of radiation exposure during a CT scanning operation thanduring a CBCT scanning operation. Specifically, the CBCT scanner 102 mayhave a quicker rotation motion compared to the spiral motion of the CTscanner 101, leading to lower doses of radiation during a CBCT scanningoperation. Further, in a CT scanning operation, a patient may need tolie down on a scanning table, while a CBCT scanning operation may allowthe patient to stand freely within the CBCT scanner's gantry. Thus, whena CT scanning operation and a CBCT scanning operation are performed onthe same scanning object, the CT images and CBCT images may need to beregistered under a common coordination system.

FIG. 2 shows a block diagram illustrating an exemplary system configuredto improve CT to CBCT registration, in accordance with certainembodiments of the present disclosure. In FIG. 2 , a CT scanner 210 mayperform a CT scanning operation on an object (e.g., a patient), andgenerate a set of CT Images 230, and a CBCT scanner 220 may perform aCBCT scan operation on the same object to generate a set of CBCT images240. A registration-enhancement system 250 may take the CT images 230and CBCT images 240 as inputs, perform a Deformable Image Registration(DIR) operation based on the CT images 230 and the CBCT images 240, andgenerate a set of registered images 260 that have enhanced quality. Theregistered images 260 may be used to for diagnostic purposes and medicaltreatments including dose accumulation, contour propagation,mathematical modeling, automatic segmentation, and functional imaging.

In some embodiments, the registration-enhancement system 250 may beconfigured to perform an enhanced Deformable Image Registration (DIR)operation based on the CT images 230 and the CBCT images 240, andgenerated one or more registered images 260. “Image registration” or“registration” may refer to a process of transforming different sets ofdata into one coordinate system. DIR may refer to a process to locallyregister one image data set into a reference image set. In other words,DIR is a process of finding a point-to-point spatial correspondencebetween two or among multiple sets of images, and finding a mappingbetween positions in one image and the positions in another image. Forexample, the DIR process may find the geometric correspondence betweenthe multiple sets of images that differ in time, space, modality, andeven subject.

In some embodiments, the registration-enhancement system 250 may performthe DIR to map one of the CT images 230 with a corresponding one of theCBCT image 240, and generate one corresponding registered image 260 thatcontains multiple deformation vector fields (DVFs) defining the motionsof each image pixel (or image voxel) from the CT image 230 to the CBCTimage 240. Alternatively, the registration-enhancement system 250 mayperform a reverse DIR to map one of the CBCT images 240 with acorresponding one of the CT image 230, and generate a correspondingregistered image 260 that contains DVFs defining the motions of eachimage pixel (or image voxel) from the CBCT image 240 to the CB image230.

In some embodiments, when performing a DIR to map a CT image to a CBCTimage, the registration-enhancement system 250 may misidentify the imagedata that is outside of the illuminated region of the CBCT image asmeaningful image data associated with water or air, or misinterpret theboundary of the illuminated region of the CBCT image as a skin-to-airboundary. Such misidentification or misinterpretation may lead to thegenerating of a mis-coordinated registered image. In some embodiments,the registration-enhancement system 250 may perform the enhanced DIRprocess to reduce or eliminated the potential misidentification ormisinterpretation due to the restricted illuminated region in the CBCTimage.

In some embodiments, the registration-enhancement system 250 may includeone or more processors 251, memory 252, and/or other components, so thatit could perform the enhanced DIR operation based on the CT images 230and the CBCT images 240. The processor(s) 251 may include centralprocessing units (CPUs) for controlling the overall operation of theregistration-enhancement system 250. The processor(s) 251 may accomplishthis by executing software or firmware stored in memory 252. Theprocessor(s) 251 may be or may include, one or more programmablegeneral-purpose or special-purpose microprocessors, digital signalprocessors (DSPs), programmable controllers, application specificintegrated circuits (ASICs), programmable logic devices (PLDs),graphical processing units (GPUs) or the like, or a combination of suchdevices. The memory 252 may represent any form of random access memory(RAM), read-only memory (ROM), flash memory (as discussed above), or thelike, or a combination of such devices. In use, the memory 252 maycontain, among other things, a set of non-transitory machine-readableinstructions which, when executed by the processor 251, causing theprocessor 251 to perform at least some embodiments of the presentdisclosure.

FIG. 3 illustrates details of a registration-enhancement system forimproving CT to CBCT registration, in accordance with certainembodiments of the present disclosure. In FIG. 3 , theregistration-enhancement system 250 may be configured to perform anenhanced DIR operation on the CT images 230 and the CBCT images 240. Theregistration-enhancement system 250 may contain, among other elements,an image-receiving module 310, a mask-generating module 320, and a DIRmodule 330. The modules contained in the registration-enhancement system250 may be implemented either as hardware components or softwareapplications running on a suitable computer. Further, some of the abovemodules may be combined into a single module, or a single module may bedivided into additional sub-modules not shown in FIG. 3 . Forconvenience purposes, the CT images 230, CBCT images 240,registration-enhancement system 250, and the registered image 260correspond to their respective counterparts in FIG. 2 .

In some embodiments, the image-receiving module 310 of theregistration-enhancement system 250 may be configured to receive a setof CT images 230 and a corresponding set of CBCT images 240. The CTimages 230 and the CBCT images 240 may be generated based on a commonobject (e.g., the same patient). Specifically, each one of the CT images230 may be associated with one or more of the CBCT images 240. In otherwords, each one of the CT images 230 may contain image datacorresponding to body regions and organs, and such image data may matchor supplement image data contained in one or more of the CBCT images 240that corresponding to the same body regions and organs. Likewise, eachof the CBCT images 240 may be associated with one or more of the CTimages 230.

In some embodiments, the image-receiving module 310 may select aspecific CT image 311 from the CT images 230, and a specific CBCT image313 from the CBCT images 240 for DIR processing. In some situations,even though associated with the same scanning object, the CT image 311typically contains the entire anatomy within the field-of-view of the CTscanner, the CBCT image 313 may contain a number of pixels that arelimited by the cylindrical volume of the CBCT scanner. Theimage-receiving module 310 may transfer the CBCT image 313 to themask-generating module 320 for generating an image mask 321 based on theCBCT image 313. Afterward, the image-receiving module 310 may transmitthe CT image 311 and the CBCT image 313 to the DIR module 330, and themask-generating module 320 may concurrently transmit the image mask 321to the DIR module 330. The DIR module 330 may then generate acorresponding registered image 260 by performing an enhanced DIRoperation based on the CT image 311, the CBCT image 313, and the imagemask 321 that is generated based on the CBCT image 313.

FIG. 4 illustrates an example scenario to construct and utilize an imagemask during an enhanced DIR operation, in accordance with certainembodiments of the present disclosure. In FIG. 4 , aregistration-enhancement system (similar to the registration-enhancement250 of FIG. 2 ) may first generate (401) an image mask 420 based on aCBCT image 410. Afterward, the registration-enhancement system may applythe image mask 420 on the CBCT image 410 to generate an output that canbe illustrated by the CBCT image with-image-mask-applied 430.

In some embodiments, the CBCT image 410 may contain a 2D set of pixels.Each “pixel” may contain a value in a 2D space representing graphicalinformation such as a Hounsfield Units (HU) value. As shown in FIG. 4 ,the CBCT Image 410 may include pixels such as pixels 411, 413, and 415.In some embodiments, the CBCT Image 410 may have an illuminated region417 that is located within the cylindrical volume of the CBCT conicalbeam. In this case, the pixels that are within this illuminated region417 may contain actual image data, while pixels that are outside of thisilluminated region 417 may contain meaningless image data. For example,the pixel 413 is within the illuminated region 417, and thereforecontains real image data generated based on the particles passingthrough a scanning object. Pixel 415 is outside of the illuminatedregion 417, and has meaningless value. In comparison, pixel 411 may beat or near the boundary of the cylindrical volume but within theilluminated region 417. Even though pixel 411 may be outside of thescanning object and contain data that represents air or water, it shouldnevertheless be treated as containing valid image data.

In some embodiments, the registration-enhancement system may generate animage mask 420 based on the CBCT Image 410. The “image mask” may containa set of data-fields having one-to-one correspondences to the set ofpixels in the CBCT image 410. Specifically, each “data-field” in theimage mask 420 may be associated with a specific pixel in the CBCT image410, and may store various information related to this associated pixel.For example, each data-field in the image mask 420 may store a valueindicating whether the associated pixel in the CBCT image 410 containsmeaningful data or not. In other words, if the data-field contains a“no-data” value, it may mean that the associated pixel does not containany image data, or that any image data contained in the associated pixelare meaningless and should be ignored. Likewise, if the data-fieldcontains a “data-existence” value, it may mean that the associated pixelcontains image data, or that the image data contained in the associatedpixel, even if equalling to zeros or null, should be treated as validand meaningful value. In FIG. 4 's example, data-field 421 may be adata-field that contains a “no-data” value, and data-field 422 may be adata-field that contains a “data-existence” value.

In some embodiments, the registration-enhancement system mayautomatically generate the image mask 420 based on Digital Imaging andCommunications in Medicine (DICOM) information stored in the CBCT images410. Specifically, the registration-enhancement system may extract, fromone or more of the CBCT images 410, DICOM information such as “DICOMReconstruction Target Center” and “DICOM Reconstruction Diameter.” TheDICOM Reconstruction Target Center 423 may refer to the center locationof the circular illuminated region formed during a CBCT scanningoperation. The DICOM Reconstruction Diameter 425 may refer to thediameter of such illuminated region.

In some embodiments, based on the DICOM information extracted from theCBCT image 410, the registration-enhancement system may generate acircular reconstruction area 427, by having the DICOM target center 423as the circle's center and the DICOM diameter 425 as the circle'sdiameter. The reconstruction area 427 may correspond to the illuminatedregion 417 of the CBCT image 410, as the reconstruction area 427 mayhave substantially the same size and location in the image mask 420 asthe size and location of the illuminated region 417 in the CBCT image410. In other words, the reconstruction area 427 may simulate andrecreate the effect of the illuminated region 417 on the CBCT scanner'sdetector panel during a CBCT scanning operation, as well as simulate thedistribution of the meaningful image data in the CBCT image 410.

In some embodiments, the registration-enhancement system may then applythe circular reconstruction area 427 to the 2D data-fields as shown inFIG. 4 . Afterward, any data-fields in the image mask 420 that arecovered by, or within the boundary of, the reconstruction area 427 maybe deemed having meaningful image data, and may be assigned with a“data-existence” value. In comparison, any data-fields in the image mask420 that are not covered by, or outside the boundary of, thereconstruction area 427 may be deemed to have meaningless image data,and may be assigned a “no-data” value. Thus, theregistration-enhancement system may assign either “no-data” value or“data-existence” value to each of the data-fields in the image mask 420by evaluating the data-fields' relative positions with respect to thereconstruction area 427 in the image mask 420. For illustrationalpurpose, in FIG. 4 , those data-fields that have “data-existence” valuesare filled with grey colors, and those data-fields that have “no-data”values are filled with white colors.

In some embodiments, the registration-enhancement system may furtherinclude a specific material type and density value in each of thedata-fields in the image mask 420, based on the HU values of the pixelsin the CBCT image 410. A data-field's material type and density valuemay determine the associated pixel's x-ray attenuation and scatteringproperties. Exemplary material types may include, without limitation,air, water, bone, adipose, lung, muscle, and cartilage. A data-field'sdensity value may then be determined based on the associated pixel'smaterial type, according to the material type's physicalcharacteristics.

In some embodiments, each of the multiple CBCT images 410 that aregenerated during a single CBCT scanning operation may contain the sameDICOM Reconstruction Target Center and DICOM Reconstruction Diameterinformation. In this case, the registration-enhancement system maygenerate one image mask 420 based on any one of the multiple CBCT images410, and apply this one image mask 420 to all of the CBCT images 410.Alternatively, the multiple CBCT images 410 that are generated duringone or more CBCT scanning operations may contain different DICOMinformation. In this situation, the registration-enhancement system maygenerate a specific image mask 420 for each of the CBCT images 410, andapply the specific image mask 420 to the corresponding CBCT image 410.

In some embodiments, after the image mask 420 is generated based on aCBCT image 410, the registration-enhancement system may utilize theimage mask 420 during a DIR operation between a CT image and the CBCTimage 410. Specifically, when performing registration of a specificpixel in the CBCT image 410, the registration-enhancement system mayextract from the image mask 420 the data-field that is associated withthe specific pixel, and evaluate the data contained therein. If theassociated data-field contains “no-data” (as shown by data-field 421),the registration-enhancement system may bypass or ignore the specificpixel of the CBCT image 410 in the DIR operation. Alternatively, if theassociated data-field contains “data-existence” (as shown by data-field422), the registration-enhancement system may further process thespecific pixel of the CBCT image 410 in the subsequent DIR operation.

In some embodiments, the outcome of utilizing the image mask during aDIR operation as described above may be shown by a CBCT image with imagemask applied 430 in FIG. 4 . For example, during the DIR operation, theregistration-enhancement system may quickly identify pixel 431 as apixel with image data, and determine that pixel 433 may be a pixel withno image data (or with meaningless image data). In this approach, theregistration-enhancement system may improve the DIR operation byignoring and eliminating the processing of any pixels that contain noimage data.

In some embodiments, when the data-field contains additional informationsuch as material type and density value, the registration-enhancementsystem may utilize such additional information to better determine thecorrespondence between the CT image and the CBCT image. Specifically,when a pixel is deemed to have image data, the registration-enhancementsystem may retrieve additional information from the data-fieldassociated with the pixel, and utilize the additional information tofurther improve the DIR operation between the CT image and CBCT image.

In some embodiments, the registration-enhancement system may alsoutilize the same enhancement process as described above to process a CTvolume which contains a set of three-dimensional (3D) cells (or“voxels”). A voxel represents a value on a fixed and regular grid in 3Dspace, and may correspond to one of the multiple 3D structures, such as,without limitation, cubes, rectangular cuboids, hexagonal structures, orstructures in any isotropic/non-isotropic shapes and sizes (e.g., 1 cm).In this case, the registration-enhancement system may reconstruct a CTvolume based on a set of CT images, and reconstruct a CBCT volume basedon a set of CBCT images. Afterward, the registration-enhancement systemmay generate a 3D image mask that contains 3D data-fields havingone-to-one associations with the voxels in the CBCT volume. The 3Ddata-fields may be used to indicate whether the corresponding voxels inthe CBCT volume has “no-data” or “data-existence” value, according tothe DICOM information in the CBCT images. The registration-enhancementsystem may then utilize the 3D image mask for the DIR processing betweenthe CT volume and CBCT volume.

In some embodiments, the above-described technique may also beapplicable for registrations between 3D images of any modality, as longas one 3D image is reconstructed from 2D projections that includes asimilar “illuminated region” as illustrated above. In other words, theregistration-enhancement system may generate a 3D image mask for the 3Dimage having the illuminated region, and utilize the 3D image mask forthe DIR processing between the 3D images without illuminated region andthe 3D image with illuminated region. Further, the above-describedtechnique may also be applicable to registration from a MR image to aCBCT/CT image.

In some embodiments, the registration-enhancement system may utilizeadditional DICOM information embedded in the CBCT images to generate anon-circular image mask. Specifically, the registration-enhancementsystem may extract DICOM information related to patient-based coordinatesystem or utilize other processing means, in order to better determinethe shape of the scanning object in the CBCT image. Afterward, theregistration-enhancement system may generate the non-circular image maskthat can further enhance the accuracy of the DIR processing.

FIG. 5 shows a flow diagram illustrating one embodiment of a process 501to improve CT to CBCT registration, in accordance with certainembodiments of the present disclosure. The process 501 sets forthvarious functional blocks or actions that may be described as processingsteps, functional operations, events, and/or acts, which may beperformed by hardware, software, and/or firmware. Those skilled in theart in light of the present disclosure will recognize that numerousalternatives to the functional blocks shown in FIG. 5 may be practicedin various implementations. In some embodiments, machine-executableinstructions for the process 501 may be stored in memory, executed by aprocessing unit, and/or implemented in a registration-enhancementsystem, such as the registration-enhancement system 250 of FIG. 2 .

One skilled in the art will appreciate that, for this and otherprocesses and methods disclosed herein, the functions performed in theprocesses and methods may be implemented in differing order.Furthermore, the outlined steps and operations are only provided asexamples, and some of the steps and operations may be optional, combinedinto fewer steps and operations, or expanded into additional steps andoperations without detracting from the essence of the disclosedembodiments. Moreover, one or more of the outlined steps and operationsmay be performed in parallel.

At block 510, a registration-enhancement system, which may be configuredto improve computed tomography (CT) to cone beam computed tomography(CBCT) registration, may receive a CT image generated by CT-scanning ofan object. The object may be a patient or an area-of-interest of apatient.

At block 520, the registration-enhancement system may receive a CBCTimage generated by CBCT-scanning of the same object.

At block 530, the registration-enhancement system may generate an imagemask based on Digital Imaging and Communications in Medicine (DICOM)information extracted from the CBCT image. In some embodiments, theDICOM information may include at least DICOM Target Center and DICOMReconstruction Diameter.

In some embodiments, for a specific pixel in the CBCT image, the imagemask contains a corresponding data-field indicating whether the specificpixel contains image data generated based on the CBCT-scanning of theobject. In other words, if the image data contained in the specificpixel is not generated by particles within a conical beam emitting fromthe CBCT scanner's beam source, or if the specific pixel is outside ofan illuminated region formed on the CBCT scanner's detector panel, thenthe image data may be deemed not generated based on the CBCT-scanning ofthe object. Otherwise, the image data may be deemed generated based onthe CBCT-scanning of the object.

In some embodiments, the registration-enhancement system may construct areconstruction area for the CBCT image based on the DICOM Target Centerand DICOM Reconstruction Diameter extracted from the CBCT image.Specifically, the reconstruction area for the CBCT image may correspondto the illuminated region formed on the CBCT scanner's detector paneland manifested in the CBCT image.

In some embodiments, upon a determination that the specific pixel isoutside the reconstruction area for the CBCT image, theregistration-enhancement system may assign a no-data value to thecorresponding data-field in the image mask that is associated with thespecific pixel. Alternatively, upon a determination that the specificpixel is inside the reconstruction area for the CBCT image, theregistration-enhancement system may assign a data-existence value to thecorresponding data-field in the image mask that is associated with thespecific pixel.

At block 540, the registration-enhancement system may generate aregistered image by utilizing the image mask to perform a DIR betweenthe CT image and the CBCT image. Specifically, theregistration-enhancement system may select a first pixel from the CBCTimage and a second pixel from the CT image. The registration-enhancementsystem may then extract from the image mask a first data-fieldassociated with the first pixel. Upon a determination that the firstdata-field contains a data-existence value, the registration-enhancementsystem may use the first pixel during the performing of the DIR.

In some embodiments, the registration-enhancement system may furtherselect a third pixel from the CBCT image and a fourth pixel from the CTimage. The registration-enhancement system may then extract from theimage mask a second data-field associated with the third pixel. Upon adetermination that the second data-field contains a no-data value, theregistration-enhancement system may ignore or skip the third pixelduring the performing of the DIR.

At block 550, the registration-enhancement system may then perform anautomatic dose estimation or a contour propagation on the object basedon the registered image. Alternatively, the registration-enhancementsystem may transmit the registered image to any third-party system forfurther processing, such as automatic image segmentation, organ andtumor localization, volume calculations, and patient positioning.

In some embodiments, organ motion that occurs during a CT and a CBCTscanning operation may lead to uncertainties in dose deliveries to thetumor and the organs at risk. Typical motion patterns may include volumeand shape changes. In this case, the registration-enhancement system mayperform the above-mentioned enhanced DIR operation to generateregistered images, which can be used to perform dose accumulation andcontour propagation for the tumor and the organs at risk. Specifically,the registration-enhancement system may utilize the registered image tobetter propagate the contours of the tumor and organs determined fromthe CT images onto the corresponding CBCT images. Likewise, theregistration-enhancement system may utilize the registered image tobetter identify regions and areas of the tumor and organs in the CTimage and CBCT images, thereby allowing a better estimation of theradioactive dosages these tumor and organs may encounter during the CTand CBCT scanning operation.

Thus, methods and systems for improving CT to CBCT registration havebeen described. The techniques introduced above can be implemented inspecial-purpose hardwired circuitry, in software and/or firmware inconjunction with programmable circuitry, or in a combination thereof.Special-purpose hardwired circuitry may be in the form of, for example,one or more application-specific integrated circuits (ASICs),programmable logic devices (PLDs), field-programmable gate arrays(FPGAs), and others.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. Those skilled in the artwill recognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure.

Software and/or firmware to implement the techniques introduced here maybe stored on a non-transitory machine-readable storage medium and may beexecuted by one or more general-purpose or special-purpose programmablemicroprocessors. A “machine-readable storage medium”, as the term isused herein, includes any mechanism that provides (i.e., stores and/ortransmits) information in a form accessible by a machine (e.g., acomputer, network device, personal digital assistant (PDA), mobiledevice, manufacturing tool, any device with a set of one or moreprocessors, etc.). For example, a machine-accessible storage mediumincludes recordable/non-recordable media (e.g., read-only memory (ROM),random access memory (RAM), magnetic disk storage media, optical storagemedia, flash memory devices, etc.)

Although the present disclosure has been described with reference tospecific exemplary embodiments, it will be recognized that thedisclosure is not limited to the embodiments described, but can bepracticed with modification and alteration within the spirit and scopeof the appended claims. Accordingly, the specification and drawings areto be regarded in an illustrative sense rather than a restrictive sense.

We claim:
 1. A method, comprising: receiving a two-dimensional (2D)computed tomography (CT) image of an object; receiving a 2D cone beamcomputed tomography (CBCT) image of the object; generating an image maskbased on the 2D CBCT image, wherein: for a specific first pixel in the2D CBCT image, the image mask contains a corresponding first data-fieldindicating that the specific first pixel contains valid image data thatare generated based on CBCT-scanning of the object, and for a specificsecond pixel in the 2D CBCT image, the image mask contains acorresponding second data-field indicating that the specific secondpixel contains invalid image data or no image data that are generatedbased on CBCT-scanning of the object; and performing a deformable imageregistration (DIR) operation to generate a registered image based on theimage mask, the 2D CT image, and the 2D CBCT image.
 2. The method asrecited in claim 1, further comprising: performing a dose estimation ora contour propagation on the object based on the registered image. 3.The method as recited in claim 1, further comprising: extractinginformation associated with an illuminated region from the 2D CBCTimage.
 4. The method as recited in claim 3, wherein the generating ofthe image mask further comprises: generating a reconstruction area forthe 2D CBCT image based on the information associated with theilluminated region; and assigning a data value to the correspondingfirst data-field in the image mask that is associated with the specificfirst pixel based on a determination that the specific first pixel iswithin a boundary of the reconstruction area for the 2D CBCT image. 5.The method as recited in claim 3, wherein the information associatedwith the illuminated region includes Digital Imaging and Communicationsin Medicine (DICOM) Reconstruction Target Center, DICOM ReconstructionDiameter, or DICOM Reconstruction Target Center and DICOM ReconstructionDiameter.
 6. The method as recited in claim 4, wherein the generating ofthe image mask further comprises: assigning a material type and densityvalue associated with the specific first pixel to the correspondingfirst data-field in the image mask based on a Hounsfield Units (HU)value of the specific first pixel.
 7. The method as recited in claim 1,wherein the generating of the registered image further comprises:selecting the first pixel from the 2D CBCT image and the second pixelfrom the 2D CT image; extracting from the image mask the firstdata-field associated with the first pixel, and the second data-fieldassociated with the second pixel; and determining to use the first pixelto perform the DIR operation based on a data value assigned to the firstdata-field, and determining to bypass the second pixel for the DIRoperation based on a data value assigned to the second data-field.
 8. Amethod, comprising: receiving a plurality of two-dimensional (2D)computed tomography (CT) images of an object; receiving a plurality of2D cone beam computed tomography (CBCT) images of the object; generatingan image mask based on a specific 2D CBCT image selected from the 2DCBCT images, wherein: for a specific first pixel in the specific 2D CBCTimage, the image mask contains a corresponding first data-fieldindicating that the specific first pixel contains valid image data thatare generated based on CBCT-scanning of the object, and for a specificsecond pixel in the 2D CBCT image, the image mask contains acorresponding second data-field indicating that the specific secondpixel contains invalid image data or no image data that are generatedbased on CBCT-scanning of the object; and performing a deformable imageregistration (DIR) operation to generate one of a plurality registeredimages based on the image mask, one of the plurality of 2D CT images,and the specific 2D CBCT image.
 9. The method as recited in claim 8,further comprising: extracting information associated with anilluminated region from the specific 2D CBCT image.
 10. The method asrecited in claim 9, wherein the generating of the image mask furthercomprises: generating a reconstruction area for the specific 2D CBCTimage based on the information associated with the illuminated region;and assigning a data value to the corresponding first data-field in theimage mask that is associated with the specific first pixel based on adetermination that the specific first pixel is within a boundary of thereconstruction area for the specific 2D CBCT image.
 11. The method asrecited in claim 10, wherein the information associated with theilluminated region includes Digital Imaging and Communications inMedicine (DICOM) Reconstruction Target Center, DICOM ReconstructionDiameter, or DICOM Reconstruction Target Center and DICOM ReconstructionDiameter.
 12. The method as recited in claim 11, wherein the informationassociated with the illuminated region extracted from each of theplurality of 2D CBCT images includes identical DICOM Target Center andDICOM Reconstruction Diameter.
 13. The method as recited in claim 11,wherein the generating of the image mask further comprises: assigning amaterial type and density value associated with the specific first pixelto the corresponding first data-field in the image mask based on aHounsfield Units (HU) value of the specific first pixel.
 14. The methodas recited in claim 8, wherein the generating of the registered imagefurther comprises: selecting the first pixel from the 2D CBCT image andthe second pixel from the 2D CT image; extracting from the image maskthe first data-field associated with the first pixel, and the seconddata-field associated with the second pixel; and determining to use thefirst pixel to perform the DIR operation based on a data value assignedto the first data-field, and determining to bypass the second pixel forthe DIR operation based on a data value assigned to the seconddata-field.
 15. A registration-enhancement system, comprising: aprocessor; and a non-transitory computer-readable medium having storedthereon instructions that, in response to execution by the processor,cause the system to: receive a two-dimensional (2D) computed tomography(CT) image of an object; receive a 2D cone beam computed tomography(CBCT) image of the object; generate an image mask based on the 2D CBCTimage, wherein: for a specific first pixel in the 2D CBCT image, theimage mask contains a corresponding first data-field indicating that thespecific first pixel contains valid image data that are generated basedon CBCT-scanning of the object, and for a specific second pixel in the2D CBCT image, the image mask contains a corresponding second data-fieldindicating that the specific second pixel contains invalid image data orno image data that are generated based on CBCT-scanning of the object;and perform a deformable image registration (DIR) operation to generatea registered image based on the image mask, the 2D CT image, and the 2DCBCT image.
 16. The registration-enhancement system of claim 15, whereinthe non-transitory computer-readable medium has stored thereonadditional instructions that, in response to execution by the processor,cause the system to: extract information associated with an illuminatedregion from the 2D CBCT image.
 17. The registration-enhancement systemof claim 16, wherein the instructions that cause the system to generatethe image mask further cause the system to: generate a reconstructionarea for the 2D CBCT image based on the information associated with theilluminated region; and assign a data value to the corresponding firstdata-field in the image mask that is associated with the specific firstpixel based on a determination that the specific first pixel is within aboundary of the reconstruction area for the 2D CBCT image.
 18. Theregistration-enhancement system of claim 16, wherein the informationassociated with the illuminated region includes Digital Imaging andCommunications in Medicine (DICOM) Reconstruction Target Center, DICOMReconstruction Diameter, or DICOM Reconstruction Target Center and DICOMReconstruction Diameter.
 19. The registration-enhancement system ofclaim 17, the instructions that cause the system to generate the imagemask further cause the system to: assign a material type and densityvalue associated with the specific first pixel to the correspondingdata-field in the image mask based on a Hounsfield Units (HU) value ofthe specific first pixel.
 20. The registration-enhancement system ofclaim 15, wherein the instructions that cause the system to generate theimage mask further cause the system to: select the first pixel from the2D CBCT image and the second pixel from the 2D CT image; extract fromthe image mask the first data-field associated with the first pixel, andthe second data-field associated with the second pixel; and determine touse the first pixel to perform the DIR operation based on a data valueassigned to the first data-field, and determine to bypass the secondpixel for the DIR operation based on a data value assigned to the seconddata-field.